I am looking forward to working with you and hope that you will find the course both enjoyable and informative.
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- Introduction
- Welcome Message
- Course Description
- Course Structure, Ingredients & Learning Objects
- This Course Relevancy's to Your Other Courses
- The School's Mission and the Course Objectives
- Learning Style for this Course
- Student-to-Student: Your Fellow Students' Opinion and Advice
- What Math Do I Need for this Course?
- Required Textbook, Recommended Readings, & Computer Package
- Computer-assisted Learning: WinQSB Package
- Course Requirements, Grading Criteria & System
- Instructions for Homework Assignment
- Homework Assignment to Do Before Each Class Meeting and Sample Tests
- JavaScript E-labs Learning Objects
- Previously-asked Questions (PAQ)
- Business Keywords and Phrases
- Compendium of Web Site Reviews
- JavaScript E-labs Learning Objects
- My Online Books’ Reviews
Introduction
Students may visit Professor Hossein Arsham in his office located in the Business Center 479. The professor can be contacted by phone at 410-837-5268, fax 837-5722, or by E-mail. To learn more information about Dr. H. Arsham, you may visit his Home Page at http://home.ubalt.edu/ntsbarsh/index.html.You may seek services (free-of-charge) tutorial help from the Academic Resource Center (ARC) at Academic Center Room 116 or by calling at (410) 837 - 5385. Professor Yoosef Kkhadem is the Coordinator of Math Service at ARC. He is knowledgeable, and has both experienced and patient. We are fortunate to have him as the tutor for this course.
If you do well in this course and would consider tutoring students in future semesters, please send an Email to the Academic Resource Center.
Dear Student and Decision-Maker
Welcome to: Applied Management Science: Making Good Strategic Decisions
I look forward to working with you and hope that you will find the course both enjoyable and informative.
In our increasingly complex world, the tasks of the decision-makers are becoming more challenging every day. The decision-maker must respond quickly to events that take place at an ever-increasing speed. A decision-maker must incorporate an often bewildering array of choices and consequences into his or her decisions.
The Web site for this course was designed and created for you. No one need be ashamed of what he or she does not know or how long it takes to master new information. Learning by the Web-enhanced course material can be self-paced and non-judgmental. Using advantages of this technology to expand learning opportunities is especially crucial because we live in a time when learning is a necessity and no longer a luxury.
At one time, it was sufficient for a firm to produce a quality product. As competition grows in today's market, simply producing a quality product is not sufficient. Today, a firm must produce a quality product at less cost than its competitors and simultaneously manage inventory, warehouse space, procurement requirements, etc. In the future, still greater demands will be placed upon decision-makers.
A manager makes many decisions everyday. Some decisions are routine and inconsequential, while others may impact the operations of a firm. Some decisions cause a firm to lose or gain money or determine whether goals are reached. The field of Decision Science (DS), known also as Operations Research (OR), Management Science (MS), and Success Science (SS), has helped managers develop the expertise and tools to understand decision problems, put them into mathematical terms and solve them. Many tools and techniques help individuals and organization make better decisions. This course provides decision makers and analysts the tools that provide a logical structure to understand the mathematical techniques to solve formulated (i.e. modeled) problems. The primary tools are linear programming and decision analysis, which provide structure and value in helping define and under-stand a problem. In this course you will learn OR/MS/DS/SS methodologies to determine optimal strategic solutions to described problems. Personal Computers allow application of these techniques even in the small business environment. Finally, a clear understanding of a general approach to problem solving enables you to use other applied decision-making and planning techniques in this course.
Since the strategic solution to any problem involves assumptions, it is necessary to determine how much the strategic solution changes when the assumptions change. You learn this by performing "what-if" scenarios or sensitivity analysis.
Preparation for management, whether it is related to technology, business, production, or services, requires knowledge of tools, which aid in determining feasible and optimal policies. In addition to communication and qualitative reasoning skills, enterprises wishing to remain competitively viable in the future, need decision support systems to help them understand the complex interactions between all components of an organization's internal and external system. Such components are found in environmental design, transportation planning and control, facilities management, military mission planning and execution, disaster relief operations, investment management, and manufacturing operations.
An organization, like other organisms, must keep itself in a state of homeostasis--subsystems regulate one another so none of the parts is ahead or behind the system as a whole. This interaction is not trivial; mathematical modeling assists in understanding these fundamental relationships. OR/MS/DS/SS concepts focus on communication of results and recommended action. This helps build a consensus concerning the possible outcomes and recommended action. The decision-maker might incorporate other perspectives of the problem, such as culture, politics, psychology, etc., into the management scientist's recommendations.
The creation of management science software is one of the most important events in decision-making. OR/MS/DS/SS software systems are used to construct examples, to understand existing concepts, and to find new managerial concepts. New developments in decision-making often motivate developments in solution algorithms and revisions of software systems. OR/MS/DS/SS software systems rely on a cooperation of OR/MS/DS/SS practitioners, algorithms designers and software developers.
This course overviews the major quantitative modeling tools successfully used to model the complex interactions described above. Although not exhaustive, this course provides framework for further study. The following tools will be studied: analytically based solutions to math models, linear programming, decision theory, integer programming and network models. Management Science encompasses many disciplines of study because decision-making is a central human activity. Appreciation of decision making is wonderful: it makes what is excellent in this thinking process belongs to you as well. Just like you, most of your classmates are employed full time. They are engineers, doctors, lawyers, and other professionals. You and your classmates want to learn the business side of their professions. It is important to learn the language of the managers to overcome communication barriers. For example, engineers will learn how to translate "precision" into extra dollars in earning/saving.
In each class I teach, there are some students who find it difficult to rethink and re-evaluate their pre-conceived ideas. In decision-making, one must have an open-mind to be able to think differently and to see from many perspectives. University classrooms provide the environment for debate and the exchange of ideas. Open-mindedness is the main requirement in achieving the ultimate goal of education, which is to be able to think for yourself. Change of opinion is often the progress of sound thought and growing knowledge.
Upon completion of this course, you may find that it "validates" what you think about making good strategic decisions and causes a peace of mind. The contents of this course will help you to systematize what you already know from your own professional experience.
For my teaching philosophy statements, visit the Web site On Learning & Teaching.
Feel free to contact me via phone, faxes, or email. There is a lot of material to cover, so let's start now!
Course Description
Management science approaches in organizations, including modeling and rational approaches to decision-making process. Emphasizes analysis and communication, using real world applications and cases. Topics include linear programming and its extensions; integer programming; network problems; decision analysis as applied to tactical and strategic business decisions. Implementation using existing software packages for management science to understand concepts and solve various managerial problems is an integrated part of this course.
Course Structure, Ingredients & Learning Objects
Course Structure: Your course materials are divided into seven ordered sections:(For your weekly homework, visit the Homework Assignment section on this site).
- The Foundation of Decision-Making Process: When one talks of "foundations", usually it includes historical, psychological, and logical aspects of the subject.
- Overcoming Serious Indecisiveness: Behavioral aspect of making hard decisions and how modern managers think on tough decisions and opportunities.
- Quantitative Tools for Modeling: Our high-school math review including Analytical Geometry, and Working with Numbers, and High School Operations Research.
- Deterministic Modeling: How to get what you expect. Course materials in this part will be presented in the context of a production and operations management applications with economics implications of the optimal decision. Our case study is the decision problem of allocating scarce resources among competitive means.
- Deterministic Models: It includes the linear optimization of Network Models and Integer Programs.
- Probability and Statistics for Modeling Risky Decisions: The needed review of your Business Statistics.
- Probabilistic Modeling: Decision making under uncertainty, i.e., what you expect you may not get. Materials in this part of the course will be presented in the context of financial portfolio selections, and marketing a new product decisions.
Course Ingredients: The Course Ingredient Components Include:
- A set of Technical Keywords and Phrases,
- A Collection of Problem-Solving Methodologies, and
- Managerial Interpretations, Their Implications and Applications.
Learning Objects: There are varieties of sources in helping you to understand the foundation of decision making. Each of the following items provides you with different perspectives on our weekly topics.
- Textbook: Your textbook is the main source reading and the exercise before each class meeting.
- Lecture Notes: Lecture notes are not your textbook substitute. They are designed to meet your needs, as I perceive while lecturing.
- Live Lectures & Handouts: The lectures are the bases of your interactions as a learning process, with your classmates and me.
- External Web Sites: The external weekly Web sites are directly relevant to the topics of the week. These reviews serve you as specialized "invited speakers" to our classroom.
- Computer Assisted Learning: My teaching style deprecates the 'plug the numbers into the software and let the magic box work it out' approach. The software is an effective tool for experimentation in serving your needed "hands on experience" for understanding the managerial implication of the concepts for yourself.
I am sure that your careful readings and effective use of the above learning objects, provide various perspectives, create a deep understanding of the topic, together with the wholeness and manifoldness of this course.
Required Textbook, Recommended Readings, & Computer Package
Required Textbook: Applied Management Science: Modeling, Spreadsheet Analysis, and Communication for Decision Making,
by Lawrence J., Jr., and B. Pasternack
John Wiley & Sons, 2nd edition, 2002, ISBN: 047126332 X.With the purchase of this book you will also receive the WinQSB Decision Support Software for MS/OM. The WinQSB is the Windows version of the QSB (Quantitative Systems for Business) software package runs under the CD-ROM Windows. There is no learning-curve for this package, you just need a few minutes to master its useful features.
The WinQSB Decision Support Software for MS/OM is also available separately from the John Wiley & Sons publisher, ISBN 0-471-40672-4, 2003.
Your textbook is available at the UB Bookstore, (410) 837-5604. Copies of the textbook are available at the "Reserved Books" section of the Langsdale Library.
The textbook chosen for this course is excellent. It is a modern, well-written and clear account of the issues facing decision makers doing business. It is easy to read, has broad coverage and is eminently suitable for self-study with many applications.
Notice that the Topics Web site units contain my weekly lecture notes. The purpose of these units is not to replace your textbook. Rather, its purpose is to provide you with other perspectives on the same topics to enhance your deep understanding.
Recommended Readings: I strongly recommend a reading of the following books:
Linstone H., Decision Making for Technology Executives: Using Multiple Perspectives to Improved Performance, Artech House, SBN: 0890064032, 1999. A copy of this book is also available as "a reserve item" for your use upon request at the Langsdale Library.
Mingers J., and A. Gill, (Eds.), Multimethodology: The Theory and Practice of Integrating Management Science Methodologies, Wiley & Sons, 1997. A copy of this book is also available at the Langsdale Library.
Some other Management Science textbooks are located on the following stacks: HD28, HD30, HD31, QA402, and T56, also Decision making Video: Values and goals, Alternatives and information, Outcomes and actions, HD30.23.D43 1987 VC, at the Langsdale Library.
Computer Package: The WinQSB is available on the the University NT server (free-of-charge). Unfortunately, one cannot access the system remotely. To use the system you need an NT account. To obtain your NT account see the Technical Assistance (TA) at the lower level of Business Center. After obtaining your username and a password then you can access the NT system. To reach the QSB, click on Start, choose the Business School Applications, then click on the Shortcut to QSB, or QSB. Then, pick-up the application you wish. All WinQSB applications are therein.
This Course Relevancy's to Your Other Courses
Today's business decisions are driven by data. There is an amazing diversity of data in all aspects of our lives and in business. Business managers and decision makers are encouraged to justify their decisions based on data. MBA graduates with strong quantitative skills are in demand. This demand increases as the impetus for model-based decisions strengthens and the amount and accessibility of data increases. The quantitative toolkit is developed and enhanced at all stages of your career. Every course in the MBA program deals with making good business decisions. Each course seems like a scattered piece of a puzzle. This course brings the pieces together by means of a unified, systematic, focused approach to decision-making, that is, Applied Management Science. It is magnificent to recognize the unity of various business concepts in the MBA Program.
ACCT 640: Accounting for Managerial Decisions: OPRE 640 integrates systems analysis, design and control for general decision-making in accounting systems. These systems use the General Structural Decision-Making Process for performance measures, cost of modeling, evaluation, and interactions among accounting system components.
Management is aware that the value of firms is the ultimate measure of company performance. For example, management has been using at least of the six common accounting measures as an operating guide, however, the linkage between operational planning and value is vague and complex and, therefore, difficult to apply. Managers need to have clear targets and performance measures to track progress.
ECON 640: Global and Domestic Business Environment: In OPRE we learn the "soft side" of Management Science. This is the human side of decision-making, which draws on the philosophy of decision-making, politics and psychology. This perspective of Management Science is important for the decision-maker. It is important for a decision-maker to establish goals to implement the decision that best fits the business environment. OR/MS/DS/SS also asks how an organization evaluates itself to make decisions about downsizing (decreasing current structure) and expanding (increasing current structure), organization evaluation and developmental processes.
INSS 640: Information System Technology: Three stages of the decision-making process:
- Systems analysis: understanding the problem
- Systems Design: searching for a "good strategic solution"
- Updating the solution: controlling the dynamic nature of information systems
The general approach to the decision-making process in OPRE 640 prepares students to understand Information Systems Technology from a broad perspective.
MGMT 640: Strategic Innovation and Renewal: OPRE 640 covers two types of decision-making: Personal and Public. Factual data and scientific tools are used to make "good, strategically defensible" decisions. This course helps you become a responsible decision maker to the shareholder or stakeholder via objective performance assessment and evaluation processes.
MKTG 640: Organization Creation and Growth: The decision-making process in marketing is about the development of new goods and services and technology. We study a manufacturing company that decides whether to develop a new product. Students learn a structural decision-making process to decide whether to hire a marketing consulting firm, the reliability of the consulting firm recommendation and other components for making a good marketing decision.
Course Requirements, Grading Criteria & System
Course Requirements & Grading Criteria Readings & homework 15% Computer assignment 10% Web sites review 5% Mid-term examination 30% Final examination 30% Term project 10%
| 90 - 100 | 80 - 89 | 70 - 79 | 65 - 69 | 60 - 64 | otherwise |
General Instructions
As you used to do experiments in physics labs to learn physics, computer-assisted learning enables you to use any online interactive tools available on the Internet to perform experiments. The purpose is the same, i.e., to understand managerial concepts such as the sensitivity analysis in your decision-making, by using applets which, are entertaining and educating.
The appearance of computer software, Java Applets, Online computation is one of the most important events in the process of teaching and learning concepts in model-based decision making courses. These tools allow you to construct numerical examples to understand the concepts, and to find their significance for yourself.
Computer-assisted learning is similar to the experiential model of learning. The adherents of experiential learning are fairly adamant about how we learn. Learning seldom takes place by rote. Learning occurs because we immerse ourselves in a situation in which we are forced to perform. You get feedback from the computer output and then adjust your thinking-process if needed.
Think about these questions as you review the assigned Web sites:
The reviews help you understand the concepts from your textbook and class lectures from different perspectives. To maximize your learning-to-learn process, visit The Impact of the Internet on Learning & Teaching.
I feel that the 90% of the total grade is good for you. The 10% term project provides the opportunity to use the OR/MS/DS/SS decision-making process to choose what kind of project you will work on.
Your term project must be relevant to decision-making and it is due during the last week of the semester. If you have any question or doubt about suitability of a topic, please let me know.
The following is a short sample of project topics submitted during last semester:
How to Write a Term Project: In preparing for a term project you must choose a topic relevant to this course, identify a variety of information sources, take efficient notes, begin and organize a tem project, use parenthetical documentation, prepare a works cited page, draft and revise your paper.
Your project is format free and there is no limits on the number of pages. It could be (among others): A real world application, or a critical and comparative review of a collection of Web sites on a particular topic. Management Science textbooks and journals can be found on the following stacks at the Langsdale Library: HD28, HD30, HD31, QA402, and T56 .
You may write a case-study article. Articles may be found in the Interfaces Journal , in stacks HD28.I45 in the Langsdale Library's Electronic DataBase such as Uncover, and ArticleFirst (through FirstSearch) are also good sources available at U of B.
Other Useful Electronic Resources: Other electronic databases include:
FirstSearch,
OR/MS,
Ei CompendexWeb,
Scirus: All Elsevier,
Euler,
Victor, UB: Electronic Resources.
The Interfaces Journal contains real world business applications. You may use the table of contents to find an article to review or compare. You must submit a copy of the article, a summary, and a critical review. You may include the article's strengths and weaknesses and how you would enhance the contents or presentation of the article.
You will also need graph paper, a scientific calculator, and a blue book (available at the Bookstore).
When taking your exam, present your work in detail. This will allow me to give partial credit.
The exams are not in any particular format so expect both standard numerical problem solving and conceptual type questions. The exams will test your understanding of the material covered in this course. The main purpose of taking the examinations is to find out how reflective your mind is in answering a set of questions correctly. The objective is to maximize the number of correct solutions, subject to a limited time constraint (a 2-hours session). Samples of past exams are available on this Web site for inspection.
Click here to see a Summary-sheet prepared by one of your classmates. If you think you have prepared a better one, kindly send it to me via an attached email. Thank you.
To prepare yourself for exams, review all topics, homework assignment and lecture notes.
Summary Sheets: Your mind is what your brain does. Self-consciousness is self-knowledge. The process of becoming conscious distributes what you know throughout your brain via the brain neural network branches, unlike memorizing, which connects only two nodes of the network. The availability and expansion of what you know throughout your neural network branches make the information processing of your brain accurate. Thus, you possess a reflective, brilliant knowledgeable mind.
The process of making your own summary-sheet is the idea of contemplating the topics you have learned. By definition of esthetics, the longer you contemplate on what you have learned the more beautiful the subject mater becomes. Beauty and contemplation is distinguished from other mental manifestations; contemplation is the result of the perfect apprehension of relations and topics.
Use the following Guide to prepare your Summary Sheets:
The above process helps to crystallize your mind to be reflective and responsive to questions posed about topics you've learned in this course and reinforces the topics in your mind.
To view a Summary-Sheet for the first test, prepared by one of your classmates, click here. If you think you have prepared a better one, kindly send it to me via an attached email. Thank you.
What Math Do I Need for this Course?
Don't Panic, high school math will suffice! There will be some refreshers. The following sites may help:I do recommend refreshing your knowledge about solving systems of equations by visiting Solving System of Equations.
For probability refresher visit Different Schools of Probabilities, and Probability Lessons.The probability applications we do use in this course are at Expected Value and Variance, and Multinomial Distributions Web sites.
Homework Assignment to Do Before
Each Class Meeting and Sample TestsPlease read and follow the Instructions for your homework assignment. Thank you.
We will proceed in the following sequence (Not a weekly-schedule of topics).
After you did your reading assignment, and your Web site review, then write a 2-page essay (format-free) entitled: "What is Applied Management Science?" Your essay should, among others, address some of the following questions:
Visit the following Web sites and then write a short review for each one of them:
Math and ...,
high schools math,
The Zero Saga & Confusions With Numbers.
Alternatively you may use:
The LP Grapher
Visit the following Web site and then write a short review:
Applications of Linear Programming
The Algebraic Method involves solving many linear systems of equations. When the LP problem has many variables and constraints then solving so many systems of equations by hand become very tedious and even for very large-scale problems it is an impossible task. Therefore, we need the computer to do the computations for us. One of the algorithmic and computerized approaches is The Simplex Method, which is an efficient and effective implementation of the Algebraic Method. There are well over 400 LP solvers, all of which using the Simplex method, including your software. Upon solving the LP problem by computer packages, the optimal solution provides valuable information, such as sensitivity analysis ranges.
As you know by now, this course has three ingredients: A set of Technical Keywords and Phrases, A Collection of Problem-Solving Algorithms, and Managerial Interpretations, and the most important of all their Implications and Applications to Business Decision-Making. As I pointed out this course is not about say, linear programming (LP), we are using LP as an application and as a tool. Since you have mastered, the Keywords & Phrase, and Techniques, now we are able to concentrate on the Managerial Business Decision-Making Process. The lecture note section on Managerial Interpretation of the WinQSB Combined Report deals with how to interpret and describe the computational results in computer output such as, the optimal strategic solution, sensitivity ranges, shadow prices, and other useful information for the decision-maker.
Perform some "what-if" scenarios analysis on Problem 2.7. That is, use your computer software package to do some numerical experimentation on variations of Problem 2.7. Again, this computer-assisted learning assignment provides a "hands-on" experience, which will enhance your understanding of the technical concepts, involved in various topics of controlling the problems, which we have covered. Your experimentation must include for example, Adding a New Constraint; Deleting a Constraint; Introducing a new product; and Terminating a product. This computer-assisted learning concepts provides a "hands-on" experience which will enhance your understanding of the technical concepts involved in various topics of sensitivity analysis that we have covered.
Visit the following Web sites and then write a short review for at least one of them:
OR-Notes: LP
Virtual Duality
LP Solver
LP-Explorer
View the following Web site and then write a short review for it:
Myths and Counterexamples in Linear Programming.
Network Models Read Ch. 4, and the course lecture notes. Solve at least any two of the following problems 4.1, 4.2, 4.6, 4.7, and 4.9 by implementing them on WinQSB, provide your managerial interpretation of the optimal solution for each problem.
You may ask what are the Managerial Interpretations?
Managerial Interpretations: The decision problem is stated by the decision-maker often in some non-technical terms. When you think over the problem, and finding out what module of the software to use, you will use the software to get the solution. The solution should also be presented to the decision-maker in the same style of language, which is understandable, by the decision-maker. Therefore, just do not give me the printout of the software. You must also provide managerial interpretation of the solution in some non-technical terms.
Warning: Computer solutions for the network and integer problems are valid, however the produced sensitivity results may not be valid. This is due to the facts that, among other things, these problems are Integer-LPs. Moreover, in the case of network models anyone constraint in any of these models is always redundant. Therefore, simply ignore the sensitivity analysis of the printouts.
Visit and then write a short review the following Web site:
A Tutorial on Integer.
You may also like to think about the topic of Your Term Project.
Preparation for the next week test: Your preparation is a very important undertaking in terms of integrating what you have learned each week in order to see the whole picture and inter-connectivity of the topics.
To prepare yourself for the actual test, you are advised to review all the topics we have covered, to review past homework assignment, and then prepare your own few pages of a summary sheet. The process of producing a summary sheet, helps you to crystallize your mind to be reflective and responsive to any question posed to you about the topics you've learned in this course, it also helps you to reinforce the wholeness of the topics in your mind.
To view a Summary-Sheets prepared by one of your classmates, click here. If you think you have prepared a better Summary-Sheets, kindly send it to me via an attached email. Thank you.
How stable is your decision? The computer packages such as your WinSQB, are necessary a very helpful tools for the decision maker in performing stability and sensitivity aspects of the decision whenever there is uncertainty in the payoffs and or in assigning probabilities in any decision analysis.
Probability Refresher: Visit the Probability Lessons, and Different Schools of Probabilities. Probability applications we do use in this course are at Expected Value and Variance Web site.
Visit the following Web sites and then write a short review for at least one of them:
Decision Analysis
Wise Decisions
Decision Analysis Society
Visit the following Web sites and then write a short review for at least one of them:
Decision Theory and Decision Trees
Introduction to Game Theory with Applications
Learning Style For This Course
This course requires a particular learning style known as learning-to-learn. Effective and efficient learning includes completing weekly homework assignment and learning from feedback. Knowledge conquered by thinking for yourself becomes a possession -- a property entirely our own.Unfortunately, most classroom courses are not learning systems. Instructors attempt to help their students acquire skills and knowledge with lectures, tests and memorization. Instructors "tell," which doesn't translate into usable skills. We learn by doing, failing and practicing. Computer assisted learning serves this purpose.
The change in learning in this course over the years is less emphasis on strategic solution algorithms and more on modeling processes, applications and software. This trend continues as more students with diverse backgrounds seek MBA degrees without too much theory and mathematics. Our approach is middle-of-the-road: no excess of math or software. We learn how to formulate problems prior to software usage. You should learn how to model a decision problem, first by hand and then by using software. The software should be used for two purposes:
- Computer-assisted learning concepts and techniques, and
- For large problems that are too difficult to solve by hand.
What are the most critical challenges in learning for this course?
- To refresh your high school math including linear algebra, basic statistics, and probability.
- To learn the new technology, mainly the use of software within a reasonable amount of time. The learning curve of the software we will be using is very sharp.
- To link the course materials with other courses in your MBA program.
- What is Management Science? A rational, structured approach to problem solving. It is the study of developing procedures that are used in decision-making and planning. An objective measure of performance must be identified to measure success. The objective must represent the decision-makers goal and serve as a starting point for developing a model for the problem.
- The context of modeling: What is a management science model? There are two types of models: Deterministic and Probabilistic. Deterministic modeling is linear programming for optimization while decision analysis is a probabilistic modeling tool used for problems under uncertainty.
- Model design, selection and setup: This includes justifying model selection (validation), setting assumptions, parameters, advantages and limitations of various models, considering the effects of data quality and accessibility, regulations, implicit versus explicit assumptions, computer models (verification), and sensitivity analysis.
- Input data selection and analysis: How to find data and the balance between quality, accessibility, credibility, and relevance. How to evaluate data quality and understand its impact.
- Analysis of results: How to tell if results are reasonable, sensitivity of output to changes in input, recognition of the useful life of a model.
- Cases and applications: Word Problem Formulation, Pure Integer/ Mixed-integer Linear Programs, Transportation Problem, Assignment Problem, Shortest Path Problem, Max Flow Problem, Critical Path Method in Project Management, Decision Analysis Cases.
- Communication: Clearly and accurately communicate the process and result by understanding the nature of the audience, effects of standards and regulations, use of appropriate format and media and maintenance of internal documentation.
It is axiomatic that if learning occurs, there is change in you. Change might occur in your attitude, thinking, beliefs and/or behavior. Something will have changed or else learning simply did not occur. I am sure you will be enthusiastic about the topics covered in this course throughout the semester and beyond. Enthusiasm is one of the most powerful engines of success; enthusiasm changes problems into challenges. When you study for this course, put your whole mind into it. Stamp your work with your own personality when it is submitting. Be active, energetic, honest, and remember: learning-to-learn was never achieved without enthusiasm.
The School's Mission and the Course Objectives
Merrick School of Business Mission Statement: Our mission is to prepare our diverse mix of students in collaboration with the business community to succeed in a dynamic global economy. The goal is to make excellence accessible. We achieve our mission by:
- Creating and delivering a leading edge curriculum with practical learning experiences in innovative and flexible ways;
- Maintaining intellectual currency through scholarship on business theory, practice and education; and
- Providing expertise to the private and public sectors as well as the academic community.
Course Objectives: What Do I Learn?
The general objective of the course is to assist you in understanding and applying the general process of structural decision-making and its components. Notice that, although we have multiple overall objectives for this course, this does not make our task a "multiple-objective problem", since there is no maximization nor minimization statement in any of our objectives.
Upon completing this course, you should be able to:
Student To Student:
Your Fellow Students' Opinion and AdviceThe following is a collection of comments on the value of the course from last semester's students. I am sure you will benefit from their experience and their precious advice for your success upon taking this course. As you can see, the most frequently mentioned recommendation is to keep up with the work and complete all assignment prior to coming to class.
There is much to gain from this course, given the expert methodology from the world of management science and business as well as daily life wisdom. All of this is available from Dr. Arsham and his decades of experience. You will enjoy what you will learn, and you will find this class to be extremely important for your careers.
JavaScript E-labs Learning Objects
This section is a part of the JavaScript E-labs learning technologies for decision making.Each JavaScript in this collection is deigned to assisting you in performing numerical experimentation, for at least a couple of hours as students do in, e.g. Physics labs. These leaning objects are your statistics e-labs. These serve as learning tools for a deeper understanding of the fundamental statistical concepts and techniques, by asking "what-if" questions.
Decision Making in Economics and Finance:
Probabilistic Modeling:
- ABC Inventory Classification -- an analysis of a range of items, such as finished products or customers into three "importance" categories: A, B, and C as a basis for a control scheme. This pageconstructs an empirical cumulative distribution function (ECDF) as a measuring tool and decision procedure for the ABC inventory classification.
- Inventory Control Models -- Given the costs of holding stock, placing an order, and running short of stock, this page optimizes decision parameters (order point, order quantity, etc.) using four models: Classical, Shortages Permitted , Production & Consumption, Production & Consumption with Shortages.
- Optimal Age for Replacement -- Given yearly figures for resale value and running costs, this page calculates the replacement optimal age and average cost.
- Single-period Inventory Analysis -- computes the optimal inventory level over a single cycle, from up-to-28 pairs of (number of possible item to sell, and their associated non-zero probabilities), together with the "not sold unit batch cost", and the "net profit of a batch sold".
Time Series Analysis for Forecasting
- Bayes' Revised Probability -- computes the posterior probabilities to "sharpen" your uncertainties by incorporating an expert judgement's reliability matrix with your prior probability vector. Can accommodate up to nine states of nature.
- Decision Making Under Uncertainty -- Enter up-to-6x6 payoff matrix of decision alternatives (choices) by states of nature, along with a coefficient of optimism; the page will calculate Action & Payoff for Pessimism, Optimism, Middle-of-the-Road, Minimize Regret, and Insufficient Reason.
- Determination of Utility Function -- Takes two monetary values and their known utility, and calculates the utility of another amount, under two different strategies: certain & uncertain.
- Making Risky Decisions -- Enter up-to-6x6 payoff matrix of decision alternatives (choices) by states of nature, along with subjective estimates of occurrence probability for each states of nature; the page will calculate action & payoff (expected, and for most likely event), min expected regret , return of perfect information, value of perfect information, and efficiency.
- Multinomial Distributions -- for up to 36 probabilities and associated outcomes, calculates expected value, variance, SD, and CV.
- Revising the Mean and the Variance -- to combine subjectivity and evidence-based estimates. Takes up to 14 pairs of means and variances; calculates combined estimates of mean, variance, and CV.
- Subjective Assessment of Estimates -- (relative precision as a measuring tool for inaccuracy assessment among estimates), tests the claim that at least one estimate is away from the parameter by more than r times (i.e., a relative precision), where r is a subjective positive number less than one. Takes up-to-10 sample estimates, and a subjective relative precision (r<1); the page indicates whether at least one measurement is unacceptable.
- Subjectivity in Hypothesis Testing -- Takes the profit/loss measure of various correct or incorrect conclusions regarding the hypothesis, along with probabilities of Type I and II errors (alpha & beta), total sampling cost, and subjective estimate of probability that null hypothesis is true; returns the expected net profit.
- Autoregressive Time Series -- tools for the identification, estimation, and forecasting based on autoregressive order obtained from a time series.
- Detecting Trend & Autocrrelation in Time Series -- Given a set of numbers, this page tests for trend by Sign Test, and for autocorrelation by Durbin-Watson test.
- Plot of a Time Series -- generates a graph of a time series with up to 144 points.
- Seasonal Index -- Calculates a set of seasonal index values from a set of values forming a time series. A related page performs a Test for Seasonality on the index values.
- Forecasting by Smoothing -- Given a set of numbers forming a time series, this page estimates the next number, using Moving Avg & Exponential Smoothing, Weighted Moving Avg, and Double & Triple Exponential Smoothing, &and Holt's method
- Runs Test for Random Fluctuations -- in a time series.
- Test for Stationary Time Series -- Given a set of numbers forming a time series, this page calculates the mean & variance of the first & second half, and calculates one-lag-apart & two-lag-apart autocorrelations. A related page: Time Series' Statistics calculates these statistics, and also the overall mean & variance, and the first & second partial autocorrelations.